Discretizing all variables

Instead of discretizing the continuous variables one by one, it is easier to discretize them automatically. To get a list of all the columns in Python, you can use

variables  = basetable.columns

Only variables that are continuous should be discretized. You can verify whether variables should be discretized by checking whether they have more than a predefined number of different values.

This exercise is part of the course

Introduction to Predictive Analytics in Python

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Exercise instructions

Make a list variables containing all the column names of the basetable.
Create a loop that checks all the variables in the list variables.
Complete the ifstatement such that only variables with more than 5 different values are discretized.
Group the continuous variables in 10 bins using the qcut method.

Hands-on interactive exercise

Have a go at this exercise by completing this sample code.

# Print the columns in the original basetable
print(basetable.columns)

# Get all the variable names except "target"
variables = list(____.____)
variables.remove("target")

# Loop through all the variables and discretize in 10 bins if there are more than 5 different values
for variable in ____:
    if len(basetable.groupby(____))>____:
        new_variable = "disc_" + variable
        basetable[new_variable] = pd.qcut(basetable[____], ____)
        
# Print the columns in the new basetable
print(basetable.columns)

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